Optical processing of vector and matrix data is known for its potentially highly effective computational performance capabilities and its natural adaptability to computationally intensive image processing. Images, or other spatially relatable data, may be treated as matrices composed of raster or vector scans of data elements that, at their real or effective resolution limit, are generally referred to as pixels. An ordinary image is typified by an analog picture frame taken as a cross section of an optical beam formed of a continuous series of such images. Each analog image frame typically contains an effectively continuous spatially distributed array of pixel data. Alternatively, discrete matrix data may be impressed onto a data beam by spatially modulating the cross section of a data beam in terms of, for example, either its localized intensity or polarization vector.
In any case, optical processing is of great potential value due to its fundamentally parallel processing nature. The parallelism, of course, arises due to the processing of complete images at a time. As each pixel is a separate datum, the volume of data processed in parallel is generally equivalent to the effective resolution of the image. Additionally, optical processing has the virtue of processing data in the same format that it is conventionally obtained. Typically, and for such applications as image enhancement and recognition, the data to be processed is generally obtained as a single image or as a raster scan of an image frame.
Optical data processors of the type described above are disclosed in U.S. patent application Ser. No. 502,981, filed June 10, 1983, entitled Method of Performing Matrix by Matrix Multiplication, invented by Jan Grinberg and Frederick Yamagishi; in U.S. patent application Ser. No. 713,064, filed Mar. 18, 1985, entitled Programmable Multistage Lenseless Optical Data Processing System, invented by Jan Grinberg and Bernard H. Soffer, and U.S. patent application Ser. No. 713,063, filed Mar. 18, 1985, entitled Programmable Methods of Performing Comlex Optical Computations Using Data Processing System, invented by Jan Grinberg, Graham R. Nudd, and Bernard H. Soffer.
A limitation in the use of these optical data processors is that they are not designed to perform matrix inversion. The prior art mechanizations are, for the most part, limited to matrix multiplication, correlation, and convolution.
Accordingly, it is an object of the present invention to provide new and improved optical data processing systems capable of matrix inversion. Potentially then, an optical processor may receive data directly without conventional or other intermediate processing. Since the informative value of image data increases with the effective resolution of the image and the number of images considered, the particular and unique attributes of optical processing become quite desireable.
Conventionally, optical processing is performed by projecting an image to be processed through a selected spatial mask onto an appropriate optical detector. A temporally variable mask for optical processors has been realized as a one-dimensional spatial light modulator (SLM) that, through electronic activation, effects selective alteration of the spatially distributed data impressed on a data beam by the mask. A typical SLM is in the form of a solid electro-optical element activated by a spatially distributed array of electrodes. The modulating image is effectively formed by separately establishing the voltage potential of each of the electrodes at an analog voltage corresponding to the respective intended data values.
It is another object of the present invention to provide an optical data processing system capable of matrix inversion, multiplication, addition, and combinations of these functions.